GitLab

* Add implicit_conversion

Extends the Argmax operator to handle dynamic input shapes.
Only shape function changes

Need this for when we debug and use MIGRAPHX_TRACE_EVAL() to show tuples
Without this we break when reading our buffer due to the use of visit()
This came up as part of #1283 debugging.

Extends unsqueeze and squeeze to work for dynamic input shapes
Does not handle the steps parameter
Adds some additional negative axes shape tests

Update dialect registration interface
Update 2nd build pipeline call and use full arch name

Fix problem with the contiguous operator constructing non-standard shape literals.  A non-standard literal will almost never be used, since a literal is known at compile time.  Added some comments on the intended behavior:

- literal{shape, vector} constructor with a non-standard shape is intended to keep the same ordering as the given vector. The data buffer will be populated such that when the non-standard indexing is used the original order is as given.
- literal{shape, argument} constructor directly copies the data buffer from the argument
- Changed non-standard literal fill() to use tensor_view iterators as it handles non-standard shapes now
- Changed the contiguous ref_ops_test to be more helpful

Extends the pooling operators for dynamic shape inputs

AveragePooling
GlobalAveragePooling
MaxPooling
GlobalMaxPooling
LpNormPooling
GlobalLpNormPooling
y.github.com>

Bumps [tensorflow](https://github.com/tensorflow/tensorflow) from 2.7.2 to 2.9.3.
- [Release notes](https://github.com/tensorflow/tensorflow/releases)
- [Changelog](https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md)
- [Commits](https://github.com/tensorflow/tensorflow/compare/v2.7.2...v2.9.3

)

---
updated-dependencies:
- dependency-name: tensorflow
  dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Chris Austen <causten@users.noreply.github.com>

Merging #1391 caused an extra adjust allocation pass for GPU targets. This removes that merge error.

Extends ref transpose operator for dynamic shapes
Make dynamic tests more consistent naming

* Default ROCm version set to 5.3 and schedule update due to DST for nightly build.

Disabling it untill int8 fix is in mainline from MIOpen and also so that QA tests could run migraphx-driver and unittests from MIGraphX.

Fix to stop types failing for logical_xor during our fusions. 

Extends the ref contiguous operator to handle dynamic shapes
Updates the eliminate_contiguous pass to use the dyn_output struct

* Update migraphx docker container to include half and cmake 3.24.2

* Include timestamp while tracing

Updated Multibroadcast op to have a two input version for dynamic shapes
Current dynamic shape broadcasting logic
dynamic_dimensions must be the same or one of them is {1, 1, 0} or {1, 1, 1}
Works for dyn-dyn, dyn-static, and static-static shape combinations
Changed common.cpp for multibroadcasting for binary ops with dynamic shapes
Extended binary.hpp for dynamic shapes to test the new common.cpp stuff

* free up more github runner space
* upgrade versions

Can be enabled via environment variable MIGRAPHX_ENABLE_NHWC

Allows for a model to be converted to the same opset but turn on infer_shapes through
onnx. This allows us to get an idea of what should be valid for the output of nodes
in a network.

Usecase:

python3 tools/convert_onnx_version.py --model <model_name> --opset=<same_as_model> --infer_shapes --output <new_model_name>

Newer split moves the split attribute to an input. In this case we check the
number of input args then.

Local Threads of multiples 32 were introduced in #1348
But LocalThreads that are not multiple of 64 are causing correctness issues.

Upgraded Dockerfiles and fixed tidy issues to make Ubuntu 20.04 and ROCm 5.3.0 the default 

updated GPU pad to now use JIT version.
added range functions for JIT kernels.

Fixes an observed regression error on certain Frozen Protobuf models due to PR 1280

use_dynamic_same_auto_pad was removed from convolution, but the driver models still retain the fields. This PR regenerates the files so that they are compatible again.

Reiterate the assertion on the standard shape but relax it for the multibroadcast ops deliberately inserted to explicit the broadcast.

Refactor dynamic compute
- add a compute_output_shape object that implicitly converts to a new dyn_output or shape object
- dyn_output object can handle computing the static output shape of an operator given the input arguments shapes
  change an operator's compute function to argument compute(const dyn_output& dyn_out, std::vector<argument> args) to 
  use dyn_output object

Dynamic ref unary functions
-  Included these changes to have an example of the refactored dynamic compute being used
-  Changes to unary base class to handle dynamic shapes
-  Changed elu and leaky_relu to use unary base class and pointwise JIT

* use find2.0 for the convolution
Co-authored-by: Vasilii Filippov <DrizztDoUrden@users.noreply.github.com>
Co-authored-by: Chris Austen <causten@users.noreply.github.com>

* Enable non-standard shape
* Use perfdb for non xdlops
* Fix transpose+broadcast strides
Co-authored-by: jungpark-mlir <jungwook.park@amd.com>

hipMemset is causing random failure.
hipMemsetAsync is doing the correct synchronization.